• Journal of Korea Entertainment Industry Association
• /
• v.15 no.5
• /
• pp.141-151
• /
• 2021

This study analyzed the meaning and functions of '-(으)ㄹ 것 같다' and '-나 보다' among the various semantic functions depending on the situation, and discussed ways to train speculative expressions more efficiently by expanding them from traditional teaching methods through visualizations applied visual thinking at real Korean language education. The speculative representation, which is the subject of this study, represents the speaker's speculation about something or situation, with slight differences in meaning depending on the basis of the speculation and the subject of the speculation. We propose a training method that can enhance the diversification and efficiency of teaching-learning through visualization of information or knowledge, speculative representations that exhibit fine semantic differences in various situations. Utilizing visual thinking in language education can simplify and provide language information through visualization of language knowledge, and learners can be efficient at organizing and organizing language knowledge. It also has the advantage of long-term memory of language information through visualization of language knowledge. Attempts of various educational methods that can be applied at the Korean language education site can contribute to establishing a more systematic and efficient education method, which is meaningful in that the visual thinking proposed in this study can give interest and efficiency to international students.

• Journal of Intelligence and Information Systems
• /
• v.29 no.4
• /
• pp.165-184
• /
• 2023

Recently, Deep learning analysis of unstructured text data using language models, such as Google's BERT and OpenAI's GPT has shown remarkable results in various applications. Most language models are used to learn generalized linguistic information from pre-training data and then update their weights for downstream tasks through a fine-tuning process. However, some concerns have been raised that privacy may be violated in the process of using these language models, i.e., data privacy may be violated when data owner provides large amounts of data to the model owner to perform fine-tuning of the language model. Conversely, when the model owner discloses the entire model to the data owner, the structure and weights of the model are disclosed, which may violate the privacy of the model. The concept of offsite tuning has been recently proposed to perform fine-tuning of language models while protecting privacy in such situations. But the study has a limitation that it does not provide a concrete way to apply the proposed methodology to text classification models. In this study, we propose a concrete method to apply offsite tuning with an additional classifier to protect the privacy of the model and data when performing multi-classification fine-tuning on Korean documents. To evaluate the performance of the proposed methodology, we conducted experiments on about 200,000 Korean documents from five major fields, ICT, electrical, electronic, mechanical, and medical, provided by AIHub, and found that the proposed plug-in model outperforms the zero-shot model and the offsite model in terms of classification accuracy.

• Proceedings of the Korea Contents Association Conference
• /
• 2017.05a
• /
• pp.353-354
• /
• 2017

본 연구는 2016년 1월부터 대구 경북에 소재하고 있는 저작기능장애가 있는 환자를 대상으로 구강건강행동지수와 치면세균막지수를 비교하였다. 연구결과 연구대상자들의 일반적인 특성과 교육 전 구강건강행동지수는 집단 간 유의한 차이가 없었다. 구강근기능훈련 프로그램 진행 후 QHI를 비교한 결과 진행후 통계적으로 유의하게 낮아지는 것으로 나타났다.

• MALSORI
• /
• no.63
• /
• pp.101-112
• /
• 2007

Spoken dialog system development includes many laborious and inefficient tasks. Since there are many components such as speech recognition, language understanding, dialog management and knowledge management in a spoken dialog system, a developer should take an effort to edit corpus and train each model separately. To reduce a cost for editing corpus and training each model, we need more systematic and efficient working environment. For the working environment, we propose DialogStudio as a spoken dialog system workbench.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.11 no.9
• /
• pp.909-916
• /
• 2016

The purpose of this study is to investigate the effect of swallowing training of high viscosity bolus for swallow function of stroke patients with dysphagia. This study subjects, acute stroke 18 patients, which were recruited to receive treatment in inpatient at general hospital, located in Kyunggido. Subjects were randomly allocated in experimental group and control group. Experimental group performed swallowing training of high viscosity bolus, while control group conducted Traditional dysphagia therapy. Both groups received treatment 30 minutes a day five times a week for four weeks. The assessment was conducted FDS(: Functional Dysphagia Scale), PAS(: Penetration Aspiration Scale), ASHA NOMS(: American Speech-language-hearing Association National Outcomes Measurements System Swallowing Scale) to compare swallow function for both group. Both groups showed significant improvements after intervention in all measures(p<.05). Change score between the two groups showed a significant improvement on experimental group than control group in FDS(p<.05). Swallowing training of high viscosity bolus could have a positive impact on swallow function for acute stroke patients with dysphagia.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.11
• /
• pp.6604-6612
• /
• 2014

The purpose of this study was to provide basic knowledge and a proper education-training program for hotel enterprises. The results are as follows. First, an education-training program was focused on five factors. Service quality, Job, Organization culture, Self improvement, and Language. Second, the Importance Performance Analysis Result show that Keep the Good Work variables are the Customer reception, Food hygiene, Hygienic management, Cooking, First aid, Self development, and Communication. Possible excesses include Customer satisfaction, Business vision, Brand, Prevention of sexual harassment, Multiple cultures. Finally, an education training program should focus mainly on 'Manner', 'Table manner', 'Personal hygiene' and 'Chinese'.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.3
• /
• pp.133-140
• /
• 2022

We investigate the performance of deep learning-based Korean language models on a task of predicting the score range of Korean essays written by foreign students. We construct a data set containing a total of 304 essays, which include essays discussing the criteria for choosing a job ('job'), conditions of a happy life ('happ'), relationship between money and happiness ('econ'), and definition of success ('succ'). These essays were labeled according to four letter grades (A, B, C, and D), and a total of eleven essay score range prediction experiments were conducted (i.e., five for predicting the score range of 'job' essays, five for predicting the score range of 'happiness' essays, and one for predicting the score range of mixed topic essays). Three deep learning-based Korean language models, KoBERT, KcBERT, and KR-BERT, were fine-tuned using various training data. Moreover, two traditional probabilistic machine learning classifiers, naive Bayes and logistic regression, were also evaluated. Experiment results show that deep learning-based Korean language models performed better than the two traditional classifiers, with KR-BERT performing the best with 55.83% overall average prediction accuracy. A close second was KcBERT (55.77%) followed by KoBERT (54.91%). The performances of naive Bayes and logistic regression classifiers were 52.52% and 50.28% respectively. Due to the scarcity of training data and the imbalance in class distribution, the overall prediction performance was not high for all classifiers. Moreover, the classifiers' vocabulary did not explicitly capture the error features that were helpful in correctly grading the Korean essay. By overcoming these two limitations, we expect the score range prediction performance to improve.

• Journal of The Korean Association of Information Education
• /
• v.26 no.3
• /
• pp.197-207
• /
• 2022

In this paper, we develop a machine learning based block code generation and recommendation model for the purpose of reducing cognitive load of learners during coding education that learns the learner's block that has been made in the block programming environment using natural processing model and fine-tuning and then generates and recommends the selectable blocks for the next step. To develop the model, the training dataset was produced by pre-processing 50 block codes that were on the popular block programming language web site 'Entry'. Also, after dividing the pre-processed blocks into training dataset, verification dataset and test dataset, we developed a model that generates block codes based on LSTM, Seq2Seq, and GPT-2 model. In the results of the performance evaluation of the developed model, GPT-2 showed a higher performance than the LSTM and Seq2Seq model in the BLEU and ROUGE scores which measure sentence similarity. The data results generated through the GPT-2 model, show that the performance was relatively similar in the BLEU and ROUGE scores except for the case where the number of blocks was 1 or 17.

• Journal of Korea Entertainment Industry Association
• /
• v.13 no.8
• /
• pp.495-504
• /
• 2019

Since the 2000s, the number of foreign students in Korea has increased considerably. In late 2010, the government's strategy to internationalize higher education will bring the number of foreign students to 140,000 as of 2019 and soon to 200,000 by 2023. As the number of foreign students increases, the happy life of foreign students in Korea has become a very important social issue at a time when the population is shrinking. Increasing the satisfaction level of foreign students living in Korea is a matter that should not be overlooked given that our society will face problems of globalization and population cliff in the future. Recently, the number of Vietnamese students studying in Korea has been on the rise, raising the need to pay attention to their happy study lives. In this study, I would like to suggest a plan for the happy life of Vietnamese students in Korea. To that end, 90 Vietnamese students in Korea were surveyed on their satisfaction with living, economy, welfare environment, university education, language education and overall studying abroad. Foreign students entering Korean society should also work together in terms of living, economy, welfare and education so that they can recognize themselves as a member of our society and live happily abroad.

• Therapeutic Science for Rehabilitation
• /
• v.12 no.4
• /
• pp.39-51
• /
• 2023

Objective : This study seeks to unveil the intellectual framework of research surrounding children's occupations by utilizing social network analysis of keywords from studies focused on childhood. Methods : From August 2003 to August 2023, we analyzed 3,364 keywords extracted from 270 research articles in the Korean Citation Index with the keyword "Child and Occupation" using the NetMiner program. Results : Research on children's work has increased quantitatively over the past decade. Keywords exhibiting a high degree of centrality in the realm of child occupation research included Task (0.055), Group therapy (0.040), Working memory (0.037), Intervention (0.033), Performance (0.030), Language (0.026), Ability (0.026), Skill (0.024), and Program (0.023). Notably, the weighted terms in the Word Network included Evaluation-Tool (30), School-Student (15), and Activity-Participation (15). The primary keywords from each topic in topic modeling were Activity (0.295), Disability (0.604), Education (0.356), Skill (0.478), School (0.317), Function (0.462), Disorder (0.324), Language (0.310), Comprehension (0.412), and Training (0.511). Conclusion : This study describes the trends in the domestic field of pediatric occupational research. These efforts provided valuable insights into pediatric occupational therapy in South Korea.